Jakarta, INTI - Ericsson introduced AI in RAN, a new technology that places artificial intelligence (AI) directly within the radio access network (RAN) to improve the performance, efficiency, and energy savings of 5G networks.
This solution enables telecommunications operators to optimize existing networks through software updates without having to add significant new infrastructure.
The launch of AI in RAN is a crucial step in the evolution of cellular networks amid the growing demand for AI-based services that demand faster, smarter, and more efficient connectivity.
Ericsson calls this technology a new standard for network intelligence, capable of delivering real-time AI-based decisions directly from radio and baseband devices. For Indonesia, this technology is considered relevant to help operators maximize existing 5G network investments.
According to GSMA data, the investment required for 5G development in Indonesia is estimated to reach US$18 billion (approximately Rp324 trillion), with the potential to increase to US$50 billion (approximately Rp900 trillion) by 2030.
With AI in RAN, network capacity and quality can be increased through software-based optimization. This approach is considered more efficient because it utilizes AI to automatically manage network resources according to the needs of ever-increasing data traffic.
AI in Ran to Improve Network Efficiency
President Director of Ericsson Indonesia, Nora Wahby, stated that the development of AI has created new demands for network connectivity, performance, and automation. Therefore, operators need technology that can increase efficiency while maintaining investment sustainability.
"AI is a key driver of innovation across various industries and is creating new needs for connectivity, performance, and automation. With AI in RAN, Ericsson is helping service providers leverage AI to improve network efficiency and long-term relevance, while also helping operators meet greater data demands amidst investment challenges," said Nora.
This technology uses telecommunications-grade AI models specifically designed to operate in microseconds in dynamic radio network environments. The models are trained using high-quality data, enabling them to make fast and accurate decisions to improve the user experience and network operational efficiency.
AI in RAN is also part of Ericsson's 5G Advanced development, which can be implemented in both dedicated device-based networks and Cloud RAN. These capabilities are supported by Ericsson Silicon and the latest generation of RAN Compute, which enables AI processing to run directly on radio devices with lower energy consumption.
Conclusion
Ericsson introduced AI in RAN, a technology that embeds artificial intelligence directly into the radio access network (RAN) to improve the performance, efficiency, and energy savings of 5G networks. This solution allows operators to optimize networks through software updates without the need for significant infrastructure additions. AI in RAN utilizes real-time AI models to automatically manage network resources. This technology is considered relevant for Indonesia to maximize 5G investments.
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